Energy performance of windows in high-rise residential buildings in Hong Kong

Energy and Buildings 34 (2002) 71±82

Energy performance of windows in high-rise residential buildings in Hong Kong M. Bojic*, F. Yik, P. Sat Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, PR China Received 12 March 2001; received in revised form 22 March 2001; accepted 23 March 2001

Abstract At the present time in Hong Kong in its hot and humid climate, a single pane, clear glazing is most often used in windows of tall residential buildings. During this study, we employed HTB2, detailed building heat transfer simulation software, to evaluate a decrease in the yearly cooling load (Q) and in the peak cooling-load (D) in two residential ¯ats due to different glazing single pane types and different ¯at orientations. The investigated glazing types were clear glazing, tinted glazing, re¯ective glazing, and tinted and re¯ective glazing. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Building envelope; Window glazing; Cooling load; Peak cooling load

1. Introduction In Hong Kong in its residential sector, the use of airconditioners during the long summer period and huge number of residential units to meet the demands for housing are causing a high and even rising cooling load and electricity consumption, and high peak cooling load and peak electricity-demand [1]. Any extensive electricity use yields larger energy-resource depletion through direct energy consumption. To satisfy larger peak electricity-demand, larger air-conditioner units and larger power plants are needed, which requires larger energy consumption for their construction. This all, however, impacts on the local (SOx, NOx) and global (CO2) environment adversely. It is, therefore, crucial, in designing new residential buildings and refurbishing old buildings, to aim for a higher level of energy and environmental performance, and optimization of building envelope through use of advanced glazing. Then, the energy and environmental performance of buildings may be improved, where the actual value of this improvement depends on the ¯at orientation and on the window distribution inside the ¯at. Extensive research is recorded into the performance of single and multiple windows in built environment. For single windows, this was a research into novel glazing types [2,3] and novel window systems [4,5]. For multiple windows, this * Corresponding author. Tel.: ‡852-2766-4697; fax: ‡852-2774-6146. E-mail address: [email protected] (M. Bojic).

was research into the in¯uence of glazing to energy behavior of buildings in different climates: cold one [6], and hot and humid one [7±10]. For hot and humid climate, investigated buildings were those for of®ce and commerce [7±9], and those for residence [10]. The investigations [10] in a performance of multiple windows in a high-rise residential tower employed the software MICRO-DOE2 to reveal that the electricity consumption would be reduced by maximally 17.5% when re¯ective glazing replaced the clear glazing at north and south facing windows. However, this study did not determine the peak cooling demand and did not address energy behavior of ¯ats differently oriented, of that with tinted, re¯ective glazing, and of that with windows facing more than two directions. The objective of the present investigation is to determine energy performance of multiple windows in the ¯ats of a residential high-rise building in hot and humid climate of Hong Kong. Then, the ¯ats have different glazing types in its cooled rooms, different orientations, and windows in different locations inside the ¯at. The energy performance is determined by using Q and D, which are calculated with a detailed building heat-transfer simulation program HTB2 [11]. The investigated glazing is clear or tinted or re¯ective or tinted and re¯ective. The ¯ats face eight different orientations. The windows are located on two opposite sides of ¯at (the large ¯at), and on three sides of ¯at where two of them are opposite and one of them perpendicular to their directions (the small ¯at). A decrease in Q and D is reported for three cases. First, this decrease is reported when higher

0378-7788/02/$ ± see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0 3 7 8 - 7 7 8 8 ( 0 1 ) 0 0 0 7 9 - 2

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M. Bojic et al. / Energy and Buildings 34 (2002) 71±82

Nomenclature D Q SC VDO VDT VDW VQO VQT VQW

yearly peak cooling-load (kW) yearly cooling load (kWh) shading coefficient decrease in D (%) decrease in D (%) decrease in D (%) decrease in Q (%) decrease in Q (%) decrease in Q (%)

quality glazing is used instead of clear glazing. Second, the decrease in Q and D is calculated for ¯ats with different orientation. Finally, the decrease in Q and D is reported for ¯ats with both different orientation and use of higher quality glazing instead of clear glass. In evaluating any measures for enhancing the energy performance of the envelope of residential buildings, it is important to take note of the spatial and time patterns of use of air conditioners in the residential ¯ats. Air-conditioners may be provided for some rooms, such as living rooms and bedrooms, but for other rooms, such as bathrooms and kitchens, they are seldom equipped with air-conditioners. Moreover, air conditioners in residential ¯ats may not be run at the same time. For living and dining rooms, their air-conditioners would be turned on most often in the evenings only because the residents would still be at work during daytime, and the air-conditioners would be switched off at night. Airconditioners serving bedrooms, however, could be running throughout the night. Here, the studied types of glazing are placed on the windows of the cooled rooms, while the windows of the non-cooled rooms retain the clear glazing. The ¯at may be shaded by walls of its own building and by the neighboring buildings; however, this phenomenon is not taken into account in the simulations. 2. The simulation software HTB2 In the study, the dynamic building energy model HTB2 was used to predict the cooling loads and indoor environmental conditions in the investigated ¯ats throughout the year. The model uses the ®nite difference method to solve the one-dimensional dynamic heat-conduction equation for modeling heat transfer through the envelope and partition elements. Then, the envelope and partitions are composed of windows with different glazing properties and of multiple layers of different materials. To allow an ef®cient year-round simulation, the model uses the necessary assumption similar to that in other building simulation models that the air temperature within each simulated zone is uniform. This building energy model can calculate a thermal performance of a building with multi-room ¯ats exposed to time varying climatic and occupation conditions. The

handled climatic parameters are outdoor temperature, solar gain, and shading. The model allows the user to de®ne occupancy pattern, complex cooling and heating (cooling), ventilation and in®ltration schedules, and lighting and internal load intensity patterns. In addition, it allows varying control settings during run-time, to mimic realistic occupation conditions. Predictions of HTB2 have been found to be matching well with measurements in buildings in cold and hot climate [12,13]. 3. Simulation arrangement 3.1. Investigated flats For a typical high-rise residential building in Hong Kong, Fig. 1 shows the layout of its intermediate ¯oor. Each ¯oor comprises eight apartments and a common lobby, which is not cooled. Flat 1 (designated as the small ¯at) and ¯at 2 (designated as the large ¯at) are the subjects of this simulation study. The reason is that the layout of this pair of apartments is simply a mirror image of the other pairs of apartments on the same ¯oor. The ¯ats 1 and 2 are different in size. The small ¯at has a total ¯oor area of 44.7 m2 and comprises two bedrooms, one living room, one kitchen, and one bathroom, while the large ¯at has total ¯oor area of 73 m2 and comprises one more bedroom and one more bathroom. The sizes of rooms in the investigated apartments are given in Table 1. In their cooled rooms, two ¯ats have windows facing different directions. For these ¯ats shown in Fig. 1, Table 2 contains the basic information on these windows such as their height, width, size, and orientation. Then, for these ¯ats, the size of window glazing in the cooled rooms is calculated as a function of their orientation; the calculation results are given in Table 3. These windows in the small ¯at face three directions and in the large ¯at three directions. For the small ¯at, 67.8% of these windows faces southeast, 10.7% faces northwest, which is the opposite direction to southeast, and 21.4% faces southwest, which is perpendicular direction to the southeast direction. For the large ¯at, 90.7% of these windows faces southwest, and only 9.3% of glazing faces the opposite northeast direction. The two ¯ats have different nominal orientation. The nominal orientation of a ¯at is de®ned as that faced by the facËade of the cooled rooms with the highest percentage of glazing. For the small ¯at, the nominal orientation is toward southeast because the facËade of its cooled rooms has the highest percentage (67.8%) of glazing facing southeast. For the large ¯at, the nominal orientation is toward southwest because the facËade of its cooled rooms has the highest percentage (90.7%) of glazing facing southwest. In Fig. 1, it can be seen that these facËades face the outdoor view. These differences in the percentage of glazing facing different directions may yield different behavior of these ¯ats for their same nominal orientation.

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Fig. 1. Schematic plan of the floor of the tall building with its view. The investigated flats are the flat 1 (a small flat) and flat 2 (a large flat). Here, S stands for the bedroom, L for the living (dining) room, K for the kitchen, T for the bathroom, and S1-S6, L1-L4, T1-T3, K1, and K2 for the windows.

Table 1 Size (in m2) of the investigated flats and their roomsa

3.2. Glazing types

Flat 1 (small flat)

Flat 2 (large flat)

Bedroom 1 Bedroom 2 Bedroom 3 Dining and living room Kitchen Bathroom 1 Bathroom 2

9.98 4.22 ± 18.28 4.86 4.32 ±

16.52 7.92 7.92 28.0 5.28 3.68 3.68

Total

41.66 (32.48)

73.00 (60.63)

a

Values for the cooled rooms are presented in italics.

In the investigated ¯ats, ®ve glazing types are used as: SC025, SC050, SC075, SC095, and SNGL6. Glazing type SC025 presents a tinted and re¯ective glazing with a shading coef®cient (SC) of 0.25; SC050 presents a re¯ective glazing with SC ˆ 0:5; SC075 presents a tinted glazing with SC ˆ 0:75; SC095 presents a clear glazing with SC ˆ 0:95; ®nally, SNGL6 presents a clear glass with SC ˆ 0:97. Their basic data are given in Table 4. Their characteristic properties used in the simulations are its diffuse transmittances, diffuse re¯ectances, thermal

Table 2 Window characteristics for the investigated flats Code numbera

Flat

Room typeb

Cooling

Glazing type

Length (m)

Height (m)

Area (m2)

Orientationc

S1 S2 S3 L2 L1 K1 T1 L3 S4 S5 S6 L4 T2 T3 K2

Small Small Small Small Small Small Small Large Large Large Large Large Large Large Large

S S S L L K T L S S S L T T K

Yes Yes Yes Yes Yes No No Yes Yes Yes Yes Yes No No No

Variable Variable Variable Variable Variable SNGL6 SNGL6 Variable Variable Variable Variable Variable SNGL6 SNGL6 SNGL6

1.63 1.40 1.75 2.00 0.82 1.20 0.70 2.60 1.60 1.80 2.00 0.82 0.70 0.70 0.70

1.54 1.54 1.54 1.54 1.54 1.20 1.20 1.54 1.54 1.54 1.54 1.54 1.20 1.20 1.20

2.51 2.16 2.70 3.08 1.26 1.44 0.84 4.00 2.46 2.77 3.08 1.26 0.84 0.84 2.40

Southwest Southeast-n Southeast-n Southeast-n Northwest Northwest Northwest Southwest-n Southwest-n Southwest-n Southwest-n Northeast Northeast Northeast Northeast

a

Window codes refer to the windows presented in Fig. 1. S stands for bedroom, L for living room, T for toilet, and K for kitchen. c Window orientation of flats shown in Fig. 1 is given. The flat nominal orientation is designated with ``n''. b

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Table 3 Orientation of glazing in the cooled rooms of the investigated flats Flat

1 2 1 2

Initial window orientation

(small) (large) (small) (large) a

Nominally oriented glazing

Opposite oriented glazing

908 Oriented glazing

Southeast Southwest 7.94/67.8a 12.31/90.7a

Northwest Northeast 1.26/10.7a 1.26/9.3a

Southwest 2.51/21.4a 0/0a

Total glazing (m2)

Number of orientation directions

3 2

Cooled rooms

Entire flat

11.71 13.57

14 17.65

These values are in the form: glazing area in cooled rooms (m2)/glazing area of total glazing surface in cooled rooms (%).

Table 4 Basic information on glazing used in the investigated flatsa Glass code

Glass type

Color

Coating

SC

d (mm)

SNGL6 SC095 SC075 SC050 SC025

Float glass Float glass Float glass High performance reflective glass High performance reflective glass

Clear Clear Bronze tinted Sterling clear Green tinted

No No No CS-35 SS-08

0.97 0.95 0.75 0.50 0.25

5 6 6 6 6

a

SC: shading coefficient; d: thickness.

Table 5 Simulation values for parameters of glazing Glazing type

Diffuse transmittance

Diffuse reflectance

Specific heat capacity (J/kg K)

Density (kg/m3)

Thermal conductivity (W/K m)

SNGL6 SC095 SC070 SC050 SC025

0.80 0.78 0.50 0.30 0.03

0.07 0.07 0.06 0.13 0.16

750 750 750 750 750

2500 2500 2500 2500 2500

1.05 1.05 1.05 1.05 1.05

conductances, densities, and speci®c heat capacities (see Table 5). The characteristic functions used in the simulations are that of the direct beam transmission and re¯ectance coef®cient versus the incidence angle (see Fig. 2). The effects of window shading by the building walls are ignored.

In particular ¯at, two types of glazing are used, i.e. one in the cooled rooms (bedrooms and leaving rooms) and one in the non-cooled rooms (toilets and kitchens). In the cooled rooms, the glazing would be one of four types: SC025, SC050, SC075, and SC095. In the non-cooled rooms, the glazing would be only of the SINGL6 type.

Fig. 2. Direct beam transmission and reflectance coefficients as functions of the incidence angle for different types of glazing.

M. Bojic et al. / Energy and Buildings 34 (2002) 71±82

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Table 6 Simulation values for parameters of wall and door layers Parameters

Concrete

Cement/sand plaster

Gypsum plaster

Wood

Specific heat capacity (J/kg K) Density (kg/m3) Thermal conductivity (W/K m)

653 2400 2.16

840 1860 0.72

837 1120 0.38

2093 800 0.160

3.3. Composition of flat walls For the both ¯ats, the composition of their walls will be the same. Each ¯at has the envelope and partition walls that comprised three layers of materials: a 100 mm thick concrete layer, and a 13 mm thick plaster layer on each side. For the partition walls, the both plaster layers are of gypsum, and for envelope walls, one is of gypsum and one of cement/ sand. The envelope outdoor walls have the solar-radiation absorptivity equal to 0.7. The doors are composed of two face plywood sheets of 6 mm thick, separated by a 38 mm air cavity. The characteristics of various layers of materials used in the external walls and partitions in the two ¯ats are as summarized in Table 6. 3.4. Utilization of flats The data on the ¯at utilization are required by the HTB2, namely details on ¯at occupancy, lighting use, power devices use, and air conditioners use. These details will be given in the following paragraphs. Flats 1 and 2 would be occupied by families of working adults who would use the ¯ats during night only. Flat 1 would accommodate a family of two adults. Flat 2 is assumed to be the dwelling of a three-person family. These occupancy patterns for the both ¯ats are assumed to be applicable to all days throughout the year, including Saturdays, Sundays and public holidays (see Table 7). Table 7 Occupancy patterns for the investigated flats Time (h)

00:00±06:30 06:30±07:00 07:00±10:00 10:00±11:00 11:00±12:00 12:00±13:00 13:00±16:00 16:00±17:00 17:00±18:00 18:00±19:00 19:00±20:00 20:00±21:00 21:00±23:00 23:00±00:00 a

Rooma Bedrooms 1&2

Living room

Kitchen

Bathroom

2 0.5 0 0 0 0 0 0 0 0 0 0 2 2

0 1 0 0 0 0 0 0 0 0 3 3 3 0

0 1 0 0 0 0 0 0 0 0 0.2 0 0 0

0 0.5 0 0 0 0 0 0 0 0 0.1 0.1 0.1 0.1

Values represent number of persons in the investigated rooms.

Lights in the rooms were assumed to be turned on or off during daytime and evening corresponding to their occupancy patterns, except for the bedrooms where the lights would be turned on only in the evening. The operating pattern of lighting in the rooms of these two ¯ats is published in [14]. Different power devices exist in the ¯ats that would consume either electricity or fuel but all energy will ultimately be released in the rooms as heat. Examples of such devices are home entertainment equipment and computers in the bedrooms and living rooms; and refrigerators, freezers, and washing machines in the kitchen, stoves in the kitchens, and gas water heaters in the bathrooms. The energy consumption of majority of the devices would correspond to the occupancy pattern, meaning that when a room is occupied, the energy devices in the room would be turned on. However, there are energy devices that would be used continuously irrespective of the occupancy pattern, e.g. when kitchen is not occupied, power would still be consumed by the refrigerator and the freezer. The operating pattern of power loads in the rooms of these two ¯ats is published in [14]. All the living rooms and bedrooms in the two apartments are equipped with air-conditioners, but there would not be air-conditioners for the kitchens and bathrooms. The air conditioners would operate for only 7 months in a year, from the beginning of April till the end of October. During the day, their operation would depend on the room occupancy. It was assumed that during the non-air-conditioned periods, all rooms would be naturally ventilated with open windows. The kitchens and the toilets, however, would be continuously ventilated. The ventilation rates were assumed to be 3 air-changes per hour (ach). However, when a room was air-conditioned, with windows shut, the assumed in®ltration rate for the room was 0.5 ach. 3.5. Calculated variables For the purpose of later illustrations, eight variables have been de®ned and used for description of the results: Q, D, VQT, VQO, VQW, VDT, VDO, and VDW. The variable Q stands for the yearly cooling load and D for the yearly peak cooling-load. The variables VQT, VQO, and VQW present a percentage decrease in Q; and variables VDT, VDO, and VDW present a percentage decrease in D. For easy of explanation, the variables VQT, VQO, VQW, VDT, VDO, and VDW would be de®ned in Section 4, while variables Q and D would be de®ned in the paragraphs that follow.

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The variable Q for a ¯at is calculated as Qˆ

8640 X N X QI;J

(1)

Iˆ1 Jˆ1

where QI;J stands for the cooling load (an output of HTB2) of room J during the hourly time interval I where I ˆ 1; . . . ; 8640 and J ˆ 1; . . . ; N. Here, N stands for the total number of air-conditioned rooms in the residential flat. The decrease in Q would mean a decrease in the yearly electricity consumption of the residential flat and because of this a decrease in the yearly CO2 production, which is a measure of the global environmental performance of the apartments. The variable D for a ¯at represents the maximum value among values of the predicted hourly cooling load of the ¯at during the whole year D ˆ max…QI † (2) PN where QI ˆ Jˆ1 QI;J is the cooling load of the flat at the hourly time interval I. The decrease in D would yield a decrease in a size of window-type air conditioner unit required for cooling, a size of a power plant required for electricity generation, energy consumption needed for construction of these units and the power plant, and yearly CO2 generation due to this energy consumption. 4. Results and analyzes On the basis of the apartment characteristics described above, Q and D of separate ¯ats have been predicted by using HTB2 based on hourly weather conditions in Hong Kong for year 1989, which was identi®ed to be representative year [15]. The values of Q and D are analyzed in details by calculating a decrease in Q (VQT, VQO, and VQW) and decrease in D (VDT, VDO, and VDW). This section summarizes the predicted results, which show how would Q, VQT, VQO, VQW, D, VDT, VDO, and VDW be affected for ¯ats having four different types of glazing at their external windows in their cooled rooms, for ¯ats facing eight different directions, and for ¯ats having two different sizes and window distributions. The studied glazing types are clear glass, tinted glass, re¯ective glass, and tinted, re¯ective glass. The studied ¯at orientations are southeast, south, southwest, west, northwest, north, northeast, and east. The studied ¯ats have sizes of 44.7 m2 (the small ¯at) and 73 m2 (the large ¯at). Then, the small ¯at has its windows facing three directions, and the large ¯at has windows facing two directions. 4.1. Yearly cooling load Generally, the window type, ¯at orientation, ¯at size, and window distribution inside the ¯at determine Q, and thus, an electricity consumption and environmental load for the ¯at.

Fig. 3. Yearly cooling load as a function of the flat orientation for different glazing types and for large and small flat.

In the following part of this paper, simulation data on Q are given in Fig. 3 for both ¯ats; these data serve to de®ne a critical glazing and a critical orientation for further analyses and discussion of the simulation results. In this discussion by using Figs. 4±6 and the variables VQW, VQO, and VQT, we would address a decrease in Q due to the separate effects of a glazing quality and ¯at orientation, and the joint effect of both the glazing quality and ¯at orientation. The curves of Q versus the ¯at orientation are shown in Fig. 3 for the large and small ¯ats that have windows with different glazing types. First, a general shape of these curves is similar. Each curve would exercise two minimums and two maximums. The curves for the ¯ats having the glazing with higher SC would lay higher in the ®gure. The curves for the larger ¯at would have higher Q than that for the smaller ¯at. Second, for some ¯at and some of its orientation, the critical glazing is de®ned as the glazing for which this ¯at would have the highest value of Q. Here, for all ¯at orientations and both the ¯ats, the critical glazing would be the clear one, which has SC ˆ 0:95. Third, for some ¯at and some of its glazing type, the critical orientation is de®ned as the orientation for which this ¯at would have the highest value of Q. For all glazing types used by the large ¯at, the critical orientation would be west, and for the small ¯at southwest. Fourth, for all glazing types and all ¯at orientations, some ¯at would have the highest Q when it has the critical glazing and the critical orientation. The large ¯at would have the highest value of Q (Q ˆ 7800 kWh per year) when this ¯at has the clear glass and the west orientation, and the small ¯at would have the highest value of Q (Q ˆ 4480 kWh per year) when it has the clear glazing and southwest orientation. In conclusion, we de®ned the critical glazing as the clear glazing, the critical orientation as west or southwest, and the ¯ats with the highest Q, which have both the critical glazing and orientation. To determine the separate effect of glazing type to Q, we calculate the variable VQW that presents a percentage decrease in Q when in its cooled rooms the ¯at uses glazing with lower SC instead of the critical glazing (clear glazing with SC ˆ 0:95). Then, the ¯at faces the same direction. The

M. Bojic et al. / Energy and Buildings 34 (2002) 71±82

Fig. 4. Variable VQW for different types of glazing. This variable is given for different flat orientation, and for (a) large and (b) small flat.

Fig. 5. Variable VQO as a function of the flat orientation for different types of glass and for large and small flat.

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Fig. 6. Variable VQT as a function of flat orientations for different glass types and for large and small flat.

variable VQW is given in Fig. 4 for ¯ats facing eight orientations: north, northeast, east, southeast, south, southwest, west, and northwest where Fig. 4a relates to the large ¯at and Fig. 4b relates to the small ¯at. The following facts are illustrated in Fig. 4. First, VQW steadily increases when glazing has lower SC for each ¯at and its orientation. For example, when in the large ¯at, the tinted glass replaces clear glass, VQW would range from 2.5 to 3.5%, when the re¯ective glass replaces clear glass, this value would range from 4 to 6.5%, and when the tinted, re¯ective glazing replaces clear glass, the value would range from 6.5 to 10%, where the exact values would depend on the ¯at orientation. These values for the small ¯at would be: 1.5 to 2.5, 3 to 4.5 and 4.5 to 7%, respectively. Second, for both the ¯ats, the highest values of VQW relate to the ¯ats facing either west or southwest, i.e. the critical orientations for which Q is the highest (compare Figs. 4 and 3). Third, for both the ¯ats, the lowest values of VQW relate to the ¯at orientations toward north and northeast for which Q is low (compare Figs. 4 and 3). Fourth, for both the ¯ats, the higher VQW would relate to the large ¯at. In conclusion, the highest decrease in Q of 10% would be obtained when, in the large ¯at, the clear glass is replaced by the re¯ective, tinted glass; then the ¯at faces west (the critical orientation). To determine a separate effect of the ¯at orientation to Q, we calculate variable VQO that presents a percentage decrease in Q of a ¯at when its orientation is varied. The ¯at initially faces its critical orientation. The curves of VQO versus the ¯at orientation are given in Fig. 5. Separate curves are given for the small and large ¯at when these ¯ats (in their cooled rooms) use glazing that is clear, tinted, re¯ective, and tinted and re¯ective. The following facts are illustrated by using Fig. 5. First, general shape of these curves in this ®gure is similar for both the ¯ats regardless of glazing type. Second, the maximum values in VQO would be obtained for two ¯at orientations. For instance, for the large ¯at with clear glazing, VQO would have its maximum value of around 6.1% for the north

direction and that of around 6.7% for the south direction. Third, the ¯at orientations for which VQO has its maximum values coincide with that for which Q has its minimum values (compare Figs. 3 and 5). Fourth, the minimum values of VQO would exist for the two ¯at orientations that coincide with the ¯at orientations for which Q has its maximum values (compare Figs. 3 and 5). Fifth, WQO depends on the glazing type; for the ¯ats using glazing with higher SC, WQO would be higher. For example, for the large ¯at, VQO for the south direction would range from 3 to 7% where the higher value holds for the clear glass (the critical glazing) and lower value holds for the tinted, re¯ective glass. Seventh, VQO has different value for the ¯ats of different size. For instance, for the large ¯at, a maximum value of VQO is roughly 7% for the ¯at with clear glass and the south orientation, and for the small ¯at, it is around 5.5% for the ¯at with clear glass and north orientation. In conclusion, the maximum drop in Q for the two ¯ats with different orientations (then, the compared ¯ats use the same type of glazing) would be up to 7%: the case when the large ¯at with clear glass faces the south±north direction instead of the west direction. However, when the large ¯at employs the tinted, re¯ective glass, this drop in Q would maximally reach 3%. To determine a joint effect of ¯at orientation and glazing quality to Q, we calculate the variable VQT that presents the percentage decrease in Q of the ¯at with clear glazing when its glazing is changed with the glazing with lower SC and when its orientation is changed. The ¯at initially faces its critical orientation. The ¯at with clear glass that faces the critical orientation would have the maximum Q. The curves of VQT versus the ¯at orientation for different glazing types are given in Fig. 6, where this ®gure relates to both the large ¯at and the small ¯at. The following facts are illustrated by using Fig. 6. First, the curves of VQT versus the ¯at orientation have similar shapes where each curve would have its two minimum and two maximum values. Second, for both ¯ats, VQT would have its two maximum values for orientations that coincide with the orientations for which the minimum values in Q would exist (compare Figs. 6 and 3). Third, the values of the maximum in VQT are different. For instance, for tinted, re¯ective glass in the large ¯at, the maximum value in VQT for the ¯at facing north would be 12.2% and that for the ¯at facing south 13.4%. Third, the two orientations would exist where the minimum VQT would be obtained, i.e. the maximum values of Q would exist. Fifth, VQT depends on glazing type, and for the ¯ats with glazing with lower SC, VQT would be higher. For instance, for the large ¯at facing north, VQT would vary from 6 to 12.2% where the ®rst value holds for clear glass and the second value holds for tinted, re¯ective glass, which has the lowest SC. Fourth, VQT has different values for ¯ats of different size. For instance, for the large ¯at, a maximum value of VQT is near 13% for the south direction and tinted and re¯ective glass, and for the small ¯at, a maximum value of VQO is around 10% for the ¯at with the same glazing facing north. In

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Fig. 7. Peak-cooling load as a function of the flat orientation for different glazing types for large and small flat.

conclusion, the maximum difference in Q for the two ¯ats with different both the orientation and glazing would be 13% for the ¯at with the tinted, re¯ective glazing that faces south compared to the same ¯at with clear glass that faces west. 4.2. Yearly maximum cooling demand Generally, the window type, ¯at orientation, ¯at size, and window distribution inside the ¯at determine D, and thus, the needed electricity demand of the air conditioner, and needed capacity of the power plant. In the following text, simulation results on D as a function of the ¯at orientation and glazing type are given for both ¯ats in Fig. 7; this ®gure is used to de®ne a critical glazing and a critical orientation for further analyses and discussion of the simulation results. A decrease in D is addressed due to the separate effects of a glazing quality and ¯at orientation, and the joint effect of both the glazing quality and ¯at orientation by using the variables VDW, VDO, and VDT, respectively, in Figs. 8±10. The curves of D as a function of the ¯at orientation are shown in Fig. 7 for the large and small ¯ats having windows with different glazing types. Several facts may be illustrated. First, a general shape of these curves is similar. Each curve would exercise two minimums and two maximums. In addition, this shape is similar to the shape of the curves Q versus the ¯at orientation from Fig. 3. The curves for the ¯ats having the glazing with higher SC would lay higher in the ®gure. The curves for the larger ¯at will have higher D than that for the smaller ¯at. Second, for each of its orientation, both the ¯at would have the highest D when they use the critical glazing (the clear glass). Third, the large ¯at with the glazing of the same type would have the highest value of D for its west orientation designated as the critical D-orientation for this ¯at. The small ¯at would have the highest value of D for west orientation (the critical D-orientation for the small ¯at) except for the tinted, re¯ective glazing when this orientation is southwest (then, the

critical D-orientation). Here, the term critical D-orientation is introduced because ¯ats with the highest D does not have the highest Q, i.e. the critical D-orientation is not the same as the critical orientation de®ned by using Q. Forth, for all its glazing types and ¯at orientations, the large ¯at will have the highest value of D (D ˆ 10:45 kWh) when it uses clear glass and faces west (its critical glazing and its critical D-orientation), and the small ¯at would have the highest value of D (D ˆ 6:15 kWh) when it has clear glazing and faces west. In conclusion, for ¯ats with the same orientation, we found that the clear glazing (critical) would give the highest value of D; for the ¯ats with the same glazing, the ¯ats facing west (the critical D-orientation) would roughly yield the highest value of D; and the ¯ats would have the highest D when they have the clear glazing and face west. To determine how D varies with the quality of glazing when the ¯at orientation does not vary, we calculate variable VDW that presents a percentage decrease in D for the ¯at that, in the cooled rooms, uses a glazing with lower SC instead of clear glazing (critical glazing). The curves VDW versus the glazing type are given in Fig. 8 for ¯ats with different orientation where Fig. 8a relates to the large ¯at and Fig. 8b to the small ¯at. The following facts may be noticed from these ®gures. First, higher VDW may be obtained for glass with lower SC. For example, in the large ¯at, VDW of around 4% would be for an use of the SC075 glazing instead of clear glass, above 7% for an use of the SC050 glazing instead of clear glass, and under 11% for an use of the tinted, re¯ective glass instead of clear glass when this last value would be under 9.5% for the small ¯at; then all these ¯ats face west. Second, for both the ¯ats, the highest VDW is obtained for the ¯ats facing west (their critical D-orientation), southwest, and northwest. In these directions, the ¯ats with the same glazing would also experience the highest values of D and Q (see also Figs. 3 and 7). In conclusion, the highest decrease in D of 11% is obtained for the large ¯at when its clear glass

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Fig. 8. Variable VDW as a function of the glazing type for different flat orientations: (a) large flat and (b) small flat.

Fig. 9. Variable VDO as a function of the flat orientations for different glazing types and for large and small flat.

M. Bojic et al. / Energy and Buildings 34 (2002) 71±82

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Fig. 10. Variable VDT as a function of the flat orientation for different glazing types and for large and small flat.

(the critical glazing) is replaced by the re¯ective, tinted glass; then the ¯at faces the critical D-orientation. To determine how, for the ¯at with the same glazing, D varies with the ¯at orientation, we calculate variable VDO that presents a percentage decrease in D for the ¯at when its orientation is changed. The ¯at initially faces the critical D-orientation. The curves VDO versus the ¯at orientation are given in Fig. 9 for the large and small ¯ats that use different glazing. The following facts are illustrated by using Fig. 9. First, a general shape of these curves is similar. The two ¯at orientations exist that would give the maximum values of WDO, and two orientations that would give the minimum values of VDO. For instance, the large ¯at with clear glass (the critical glazing) would have two maximum values of VDO: that of 11% when the ¯at faces south and that of 9% when the ¯at faces north. Second, the shape of these curves in Fig. 9 is similar to the shape of the curves VQO versus the ¯at orientation from Fig. 5 as the ¯at orientations for their minimum and maximum values almost coincide. Third, for the ¯ats with glazing with higher SC, VDO would be higher. For instance, for the large ¯at facing south, the highest value of VDO of 11% holds for clear glass, and the lowest value of VDO of 5% holds for the tinted, re¯ective glass. Forth, VDO differs for ¯ats of different size. For instance, for the large ¯at, the highest value of VDO is near 11% when this ¯at has clear glazing and faces south, and for the small ¯at, the highest value of VDO is around 9% when this ¯at has clear glazing and faces north. In conclusion, the maximum difference in D for two ¯ats with different orientations (then, the compared ¯ats use the same type of glazing) would be up to 11% when the ¯at with clear glass faces the south±north direction instead of the west direction. However, if the ¯at employs the tinted, re¯ective glass, then this drop in D would maximally approach 5%. To determine how D varies with the ¯at orientation and glazing type, we calculate variable VDT that presents a percentage decrease in D of a ¯at when its clear glazing is changed with the glazing of other type and when its orienta-

tion is changed. The initial orientation of this ¯at is its critical D-orientation. The ¯at with clear glazing that face the critical D-orientation would have the maximum value of D. The curves VDT versus the ¯at orientation are given in Fig. 10 for the large and small ¯at that use different glazing types. The following facts are illustrated by using Fig. 10. First, these curves have a similar shape. Each curve would have its two maximums and two minimums. The maximums in these curves correspond to minimums in the curves D versus the ¯at orientation from Fig. 7 and vice versa. These curves have the similar shape as the curves VQT versus the ¯at orientation from Fig. 6. Second, two maximums of each curve VQT versus the ¯at orientation have different values of VQT. For example, for the large ¯at with the re¯ective, tinted glass, the higher value of VDT maximum is 16% for the south orientation and the lower value of VDT maximum is 15% for the north orientation. Third, for the ¯ats with glazing with lower SC, VDT will be higher. For instance, for the large ¯at facing south, VDT would range from 11 to 16% where the ®rst value holds for the clear glass (the critical glazing) and the second value holds for the tinted, re¯ective glass, which has the lowest SC among all investigated glazing. Fourth, VDT has different values for ¯ats of different size. For instance, for the large ¯at, a highest value of VDT would be 16% for the ¯at with tinted, re¯ective glass that faces south and for small ¯at, the highest value of VDT would be 13% for the ¯at with tinted, re¯ective glass that faces north. In conclusion, the maximum difference in D for the two ¯ats with different both orientation and glazing would be 16% for the ¯at with the tinted, re¯ective glazing that faces south compared to the same ¯at with clear glass that faces west. 5. Conclusion This paper describes the investigations performed on the thermal behavior of two differently sized residential apart-

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ments in hot and humid climate in Hong Kong when the apartments would be air conditioned during ``seven'' summer months. The investigated apartments face different orientations, and possess different single-pane glazing. The investigated glazing are of the following types: clear, tinted, re¯ective, and tinted ‡ reflective. These investigations were based on the analysis of Q and D predicted by using detailed building heat transfer simulation program HTB2. Three cases are analyzed in this paper. In the ®rst case, the clear glass would be replaced by the glass with lower shading coef®cient (then, the ¯at has the same orientation). The results of the analysis indicate that the highest decrease in Q of roughly 10% and that in D of 11% would be obtained for the ¯at facing west when the clear glass is replaced by the re¯ective, tinted glass. In the second case, the difference in Q and in D would be analyzed for the two ¯ats with different orientations (then, the compared ¯ats use the same type of glazing). The highest drop in Q of up to 7% and in D of 11% is found when the ¯at with clear glass faces the south±north direction instead of the west direction. However, if the ¯at employs the tinted, re¯ective glass, then this drop in Q would maximally reach 3% and in D approach 5%. In the third case, the difference in Q and in D would be analyzed for the two ¯ats with different both the orientation and glazing. The maximum drop of 13% in Q and of 16% in D is found for the ¯at with the tinted, re¯ective glazing that faces south compared to the same ¯at with clear glass that faces west. Values of Q and D, and their investigated drops were higher for the large ¯at than for the small ¯at and had slightly different dependence with the ¯at orientation. This may be attributed to the difference in ¯at size and in window distribution inside the cooled rooms of these ¯ats; however, further investigations are required completely to describe these in¯uences. It is suggested that when trying to assess the effects of design and retro®t of a high-rise residential building in Hong Kong and in other locations with hot climates several different analyses should be performed. Required are not only analyses of the yearly cooling load and peak cooling demand of a residential ¯at, but also that of an actual energy consumption, an economic appraisal, and environmental assessment. Economic appraisal analysis takes into account the additional investments, the energy cost savings, and the cost savings due to reduction in the maximum electricity demand. The environmental assessment analyses evaluate environmental bene®ts for indoor and outdoor environment due to these design and retro®t actions.

Acknowledgements The authors wish to acknowledge the ®nancial support provided by The Hong Kong Polytechnic University under the Area of Strategic Development in the Faculty of Construction and Land Use. The work is being undertaken within the Centre for Building Environmental Performance, Department of Building Services Engineering.

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